Exploring the Potential of Reinforcement Learning in Pediatric Speech and Language Therapy
Project Overview
We are working on an innovative project to improve speech therapy for children who have trouble speaking or understanding language. We’re using a type of computer technology called Reinforcement Learning to make speech therapy more personalized and effective. This technology learns from past therapy sessions and gets better over time, offering suggestions tailored to each child’s needs. Many children around the world face challenges with speech and language, and while therapy can help, there are several obstacles like limited resources, outdated methods, and a lack of access to the latest research. Our project aims to overcome these hurdles by introducing a smart and learning system that supports therapists with up-to-date, customized strategies for helping each child improve. Through this approach, we also strive to acquire knowledge about children’s learning preferences and the most efficacious speech-language therapy techniques.
We plan to develop this system using information from previous therapy sessions and then test it in real-life settings to see how well it works. Our goal is to make speech therapy more effective, understandable, and accessible, ensuring that every child has the opportunity to communicate clearly and confidently. Our team includes experts from different fields, all working together to bring this technology to life. We believe that by combining the latest in computer science and artificial intelligence with the knowledge of speech therapists, we can make a big difference in the lives of children with speech and language disorders.
Principal Investigator
Orhan Selçuk Güven , Université de Montréal